() #102 Emory (12-6)

1150.1 (25)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
106 LSU Win 13-8 23.28 23 4.55% Counts Feb 19th Mardi Gras XXXIV
301 Houston** Win 13-5 0 17 0% Ignored (Why) Feb 19th Mardi Gras XXXIV
349 Trinity University** Win 13-4 0 17 0% Ignored (Why) Feb 19th Mardi Gras XXXIV
172 Wisconsin-Whitewater Win 13-4 15.57 7 4.55% Counts (Why) Feb 19th Mardi Gras XXXIV
161 Mississippi State Win 8-7 -5.12 26 4.05% Counts Feb 20th Mardi Gras XXXIV
106 LSU Loss 7-13 -27.01 23 4.55% Counts Feb 20th Mardi Gras XXXIV
114 Florida State Win 9-6 15.44 24 4.05% Counts Feb 20th Mardi Gras XXXIV
168 Kennesaw State Win 10-3 21.61 31 5.96% Counts (Why) Apr 9th Southern Appalachian D I College Mens CC 2022
111 Georgia State Win 8-7 5.53 25 6.06% Counts Apr 9th Southern Appalachian D I College Mens CC 2022
44 Georgia Tech Loss 5-14 -19.11 31 6.82% Counts (Why) Apr 9th Southern Appalachian D I College Mens CC 2022
134 Tennessee Loss 7-13 -50.52 28 6.82% Counts Apr 9th Southern Appalachian D I College Mens CC 2022
274 Georgia Southern Win 15-7 -5.16 18 6.82% Counts (Why) Apr 10th Southern Appalachian D I College Mens CC 2022
111 Georgia State Loss 6-11 -40.44 25 6.46% Counts Apr 10th Southern Appalachian D I College Mens CC 2022
121 Tennessee-Chattanooga Win 13-8 31.22 29 6.82% Counts Apr 10th Southern Appalachian D I College Mens CC 2022
106 LSU Win 13-9 36.23 23 8.12% Counts Apr 30th Southeast D I College Mens Regionals 2022
57 Alabama Loss 8-12 -15.66 28 8.12% Counts Apr 30th Southeast D I College Mens Regionals 2022
47 Florida Loss 7-13 -20.38 26 8.12% Counts Apr 30th Southeast D I College Mens Regionals 2022
114 Florida State Win 12-8 34.32 24 8.12% Counts Apr 30th Southeast D I College Mens Regionals 2022
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FAQ

The results on this page ("USAU") are the results of an implementation of the USA Ultimate Top 20 algorithm, which is used to allocate post season bids to both colleg and club ultimate teams. The data was obtained by scraping USAU's score reporting website. Learn more about the algorithm here. TL;DR, here is the rating function. Every game a team plays gets a rating equal to the opponents rating +/- the score value. With all these data points, we iterate team ratings until convergence. There is also a rule for discounting blowout games (see next FAQ)
For reference, here is handy table with frequent game scrores and the resulting game value:
"...if a team is rated more than 600 points higher than its opponent, and wins with a score that is more than twice the losing score plus one, the game is ignored for ratings purposes. However, this is only done if the winning team has at least N other results that are not being ignored, where N=5."

Translation: if a team plays a game where even earning the max point win would hurt them, they can have the game ignored provided they win by enough and have suffficient unignored results.